A quick guide for your next project implementation

Dell’s Kevin Terwilliger recently presented the webinar “Update Your Legacy Systems with the IIoT.”  Today he shares five best-practice steps when planning your next project

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Dell's Kevin Terwilliger

implementation:

Establish a project-success model

Choose an initial project that proposes a solution with a strong project-delivery methodology to enrich and complement business processes. A strong recipe for success is to understand how other projects have missed the mark. Build the underpinnings of the organization, the people and the process so that the technology can be delivered in a way that provides specific value. Consider these key project goals to ensure your success:

  • Start with a well-defined problem to attack
  • Get support by stakeholders who have the right expertise to get the problem solved
  • Determine ownership within your IT and OT organizations
  • Establish the ROI value and key project milestones
  • Focus on projects that can transform both adoption of new technologies as well as improvement of business processes                                                                            

Build on a strong foundation of data 

Determine what data you need and which processes and operations you want to improve. Collect and curate the data that you already have available, then add sensors to bring in real-time data that you currently do not have. Real-time insights give context through integration with systems that contain master records about equipment, such as the make/model, purchase date, when it was put into service, as well as historical information about repairs and maintenance. This valuable context provides organizations a greater level of understanding about how things operate throughout the factory. By linking these types of data sources together with IoT data from devices and sensors, you can gain even greater insight into machine performance and health.

Gain contextual visibility into operations

Establish real-time visibility into all that’s happening—where are your things, what alerts were triggered, how is the asset performing? Intelligent gateways can provide a contextual view across all assets and devices, as well as a map of locations, historical logs, reports, health and condition. All of this data enables users to tailor real-time visualizations to fit their specific needs and functional responsibilities. With granular and contextual data, manufacturers can apply network policies throughout the extended production process. Additionally, actionable data can be shared with the appropriate personnel, vendors and partners to inform and improve decision-making.

Apply rules and analytics to identify issues

Rules and analytics of all types can monitor the ongoing conditions of equipment, operations and even the surrounding environment. Known conditions, such as normal operating or expected usage patterns, can be reflected in rules that trigger when certain conditions are breached. However, there are challenges in terms of the volume and variety of the devices and data which traditional rules engines are not designed to handle. Choose a gateway that delivers a highly scalable, parallel-processing rules engine and an intuitive, visual rules editor that is simple to manage. For more complex situations, advanced predictive analytics can also help organization gain new insights from IoT data.

Automate actions when issues arise

IoT demands an increasing amount of automation—there are simply too many sensors and devices and too much data to process. Automating responses to abnormal conditions and issues is critical. Find an IoT solution with an action engine that can do basic tasks (such as send an SMS message when a rule is triggered) but also allows you to take actions through external systems. This combination provides a closed-loop response to issues in the operational environment, while providing traceability from the sensor data to the asset to the response all through a flexible automated process.

Kevin Terwilliger is solutions director for Dell’s IoT division.

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  • I personally agree that the ultimate objective of new technology adoption such as IIoT is to enrich and complement work processes; not just business processes, but also the work processes in the plant like operations and maintenance through digital transformation of how work is done. It al starts with digital transformation of technology, adopting digital networking in place of analog signals. I also agree you should start with a well-defined problem to attack; conduct a plant modernization audit to identify opportunities to improve operations with a second layer of automation. This is how it is done for plants in the process industries: https://www.linkedin.com/pulse/meet-new-demands-plant-modernization-audit-jonas-berge I personally agree it is critical to determine ownership within your IT and OT organizations; there has to be a clear boundary of responsibility. Here’s a description of where this happens in the IIoT architecture; “good fences make good neighbors”: https://www.linkedin.com/pulse/iiot-architecture-standards-every-level-lets-you-change-jonas-berge I personally agree you need to determine what data you need in order to improve processes and operations and that therefore you need add sensors to bring in real-time data that you currently do not have. If the plant supports fieldbus these sensors are easily added to existing networks. If the plant is built on 4-20 mA and on-off signals, using wireless sensors is the most practical way. Plants a are following a 6-step deployment process: https://www.linkedin.com/pulse/how-plants-get-started-iiot-jonas-berge I agree real-time insights is crucial because you need to capture developing equipment problems early, before they fail. This requires real-time analytics and it has to be easy. Learn from this essay how plants are doing it: https://www.linkedin.com/pulse/real-end-users-analytics-data-scientists-jonas-berge

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